Interference cancellation method and receiver

ABSTRACT

The invention relates to an interference cancellation method and a receiver including interference canceller for suppressing a narrow-band interference signal from a received signal, converter for performing an orthonormal conversion of the signal into subspace components of a desired subspace, a decoder connected operationally to the output of the interference canceller, in which decoder an estimate for the received signal is obtained. The output of the decoder is operationally connected to the interference canceller, and the converter is arranged to determine an estimate for narrow-band interference properties, in which determination the estimate obtained from the output of the decoder is subtracted from the received signal before the orthonormal conversion is performed. By using the determined estimate, the interference canceller is arranged to reduce effect of the subspace components including narrow-band interference signals from the received signal.

This is a continuation of U.S. patent application Ser. No. 09/971,770,filed Oct. 9, 2001 now U.S. Pat. No. 7,113,476, which is a continuationof International Patent Application PCT/FI01/00115, filed Feb. 8, 2001,which, in turn, relies for priority upon Finnish Patent Application No.20000284, filed on Feb. 10, 2000, the contents of all of which arehereby incorporated by reference in their entireties.

FIELD OF THE INVENTION

The invention relates to a receiver and a method of suppressing anarrow-band interference from a wide-band signal.

BACKGROUND OF THE INVENTION

Telecommunication connections are subject to various interferences.There are several reasons for interference. In telecommunicationconnections, the transmission path used for transmitting signals isknown to cause interference to telecommunication. This occurs regardlessof the physical form of the transmission path; whether the transmissionpath is, for instance, a radio link, an optical fibre or a copper cable.Particularly in radio telecommunication there are frequently situationswhere the quality of the transmission path varies from one connection toanother and also during a connection.

Radio path fading is a typical phenomenon that causes changes in atransmission channel. Other simultaneous connections may also causeinterferences and they can vary as a function of time and place.

To reduce effects of various interferences, several solutions have beenevolved. This is the case in radio communication in particular. Varioustelecommunication methods have been evolved, aiming at achieving as highspectral efficiency as possible and still minimising the effect ofinterference. A wireless telecommunication method which has been verymuch studied lately is a wide-band spread-spectrum multiple accessmethod CDMA (Code Division Multiple Access).

Compared to multiple access methods that were generally used earlier,the CDMA has a plurality of advantages. In a CDMA method, a narrow-banddata signal of the user is multiplied by a spreading code having aconsiderably wider band to a relatively wide band. Bandwidths used inknown experimental systems include 1.25 MHz, 10 MHz and 25 MHz. In themultiplying process, the data signal spreads to the entire band used.All users transmit simultaneously by using the same frequency band. Eachconnection between a base station and a mobile station uses its ownspreading code, and the signals of the users can be distinguished fromeach other in the receivers on the basis of the spreading code of eachuser. The aim is to select the spreading codes so that they are mutuallyorthogonal, i.e. they do not correlate with each other. The abovedescribed CDMA method is called a direct-sequence method, DS-CDMA(Direct Sequence CDMA). There are other CDMA methods as well, such as afrequency hopping method FH-CDMA (Frequency Hopping CDMA), in which thefrequency used is varied quickly according to the used spreading code. Acombination of these methods is also possible.

A problem of wide-band data transmission is narrow-band interference,which is typically caused by narrow-band signal sources external to thesystem, using the same or overlaying frequency band with the system.Typical of these interference signals is that their properties andstructure often differ from the signals of the system considerably. Theyoften use a lower data transmission rate. Also, it is often so that theproperties of interfering signals are not known in advance.

The CDMA can, to some extent, inherently compensate the effect ofnarrow-band interference on wide-band data transmission, but if theinterfering signal is much stronger than the wide-band signal, it maycause considerable interference.

To suppress narrow-band interference from a wide-band signal, variousmethods have been evolved. The publication S. Sandberg, “AdaptedDemodulation for Spread Spectrum Receivers which Employ Transform-DomainInterference Rejection”, IEEE Trans. On Communications, Vol. 43, pp2502-2510, September 1995, discloses a method in which the problem isapproached in the frequency domain, and the interference is suppressedby removing the frequencies where the interference is assumed to be. Inthe presented solution, however, the location of the interference in thefrequency band and the bandwidth of the interference are assumed to beknown. The interference is also assumed to be stationary.

The publication M. Lops, A. Tulino, “Automatic Suppression of NarrowbandInterference in Direct Sequency Spread-Spectrum Systems”, IEEE Trans. OnCommunications, Vol. 47, pp. 1133-1136, August 1999, discloses a methodin which non-stationary interference, the properties of which are notknown, can be suppressed. However, the achieved results are notqualitatively satisfactory.

BRIEF DESCRIPTION OF THE INVENTION

It is an object of the invention to implement an improved method andequipment implementing the method for interference cancellation. This isachieved by a method of suppressing narrow-band interference from awide-band signal, wherein a signal is received, an orthonormalconversion of the signal into subspace components of a desired subspaceis performed, the converted signal is decoded with a decoder, whereby anestimate for the received signal is obtained, and when an estimate fornarrow-band interference properties is determined, the estimate obtainedfrom an output of the decoder is subtracted from the received signalbefore the orthonormal conversion is performed, and, by means of thedetermined estimate, effect of the subspace components comprisingnarrow-band interference signals is reduced in the received signal.

The invention also relates to a receiver comprising interferencecancellation means for suppressing a narrow-band interference signalfrom a received signal, means for performing an orthonormal conversionof the signal into subspace components of a desired subspace, a decoderconnected operationally to the output of the interference suppressionmeans, in which decoder an estimate for the received signal is obtained.In the receiver of the invention, the output of the decoder isoperationally connected to the interference suppression means, and theconversion means are arranged to determine an estimate for narrow-bandinterference properties, in which determination the estimate obtainedfrom the output of the decoder is subtracted from the received signalbefore the orthonormal conversion is performed, and by using thedetermined estimate, the interference cancellation means are arranged toreduce effect of the subspace components comprising narrow-bandinterference signals in the received signal.

The preferred embodiments of the invention are disclosed in thedependent claims.

The invention is based on projecting the received signal onto anorthonormal subspace. A desired signal has a projection deviating fromzero onto most orthonormal bases, whereas narrow-band interference hasconcentrated on specific directions. By suitably selecting theorthonormal base and the projection to be performed, the interferencecan thus be reduced or suppressed in its entirety. By subtracting thepreliminary estimate of the desired signal from the received signal, thesubspace components on which the interference concentrates can beestimated better than before. Thus, the projection onto the orthonormalcomponents orthogonal to the interference can be performed better thanbefore. The method can be repeated iteratively many times.

BRIEF DESCRIPTION OF THE FIGURES

In the following the invention will be described in greater detail inconnection with the preferred embodiments, with reference to theattached drawings, in which

FIG. 1 shows an example of a system according to an embodiment of theinvention,

FIG. 2 shows a second example of a system according to an embodiment ofthe invention, and

FIG. 3 illustrates a system model according to an embodiment of theinvention,

FIG. 4 illustrates a structure of a receiver according to an embodimentof the invention, and

FIGS. 5 a and 5 b illustrate solutions according to preferredembodiments of the invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION

Preferred embodiments of the invention can be applied intelecommunication systems where a desired signal is transmitted andreceived as a wide-band one. Such a telecommunication system is awide-band CDMA radio system, for instance. In the following example,preferred embodiments of the invention will be described in a universalmobile telephone system employing a wide-band code-division multipleaccess method, yet without restricting the invention thereto.

With reference to FIG. 1, a structure of a mobile telephone system isexplained by way of example. The main parts of the mobile telephonesystem are core network CN, terrestrial radio access network of themobile telephone system UTRAN (UMTS terrestrial radio access network)and user equipment UE. The interface between the CN and the UTRAN iscalled Iu and the air interface between the UTRAN and the UE is calledUu.

The UTRAN comprises radio network subsystems RNS. The interface betweenthe RNSs is called Iur. The RNS comprises a radio network controller RNCand one or more nodes B. The interface between the RNC and B is calledIub. The coverage area, or cell, of the node B is marked with C in thefigure.

The description of FIG. 1 is relatively general, and so it is clarifiedwith a more specific example of a cellular radio system shown in FIG. 2.FIG. 2 only includes the most essential blocks, but it is obvious to aperson skilled in the art that the conventional cellular radio networkalso includes other functions and structures, which need not be furtherexplained herein. It is also to be noted that FIG. 2 only shows oneexemplified structure. In systems according to the invention, detailscan be different from what are shown in FIG. 2, but as to the invention,these differences are not relevant.

A cellular radio network thus typically comprises a fixed networkinfrastructure, i.e. a network part 200, and user equipment 202, whichmay be fixedly located, vehicle-mounted or portable terminals. Thenetwork part 200 comprises base stations 204. A base station correspondsto the node B shown in the previous figure. A plural number of basestations 204 are, in turn, controlled in a centralised manner by a radionetwork controller 206 communicating with them. The base station 204comprises transceivers 408 and a multiplexer unit 212.

The base station 204 further comprises a control unit 210 which controlsthe operation of the transceivers 208 and the multiplexer 212. Themultiplexer 212 arranges the traffic and control channels used byseveral transceivers 208 to a single transmission connection 214. Thetransmission connection 214 forms an interface Iub.

The transceivers 208 of the base station 204 are connected to an antennaunit 218 which is used for implementing a bi-directional radioconnection 216 to the user equipment 202. The structure of the frames tobe transmitted in the bi-directional radio connection 216 is definedseparately in each system, the connection being referred to as an airinterface Uu.

The radio network controller 206 comprises a group switching field 220and a control unit 222. The group switching field 220 is used forconnecting speech and data and for combining signalling circuits. Thebase station 204 and the radio network controller 206 form a radionetwork subsystem 224 which further comprises a transcoder 226. Thetranscoder 226 is usually located as close to a mobile servicesswitching centre 228 as possible, because speech can then be transferredin a cellular radio network form between the transcoder 226 and theradio network controller 206, which saves transmission capacity.

The transcoder 226 converts different digital speech coding forms usedbetween a public switched telephone network and a radio network to makethem compatible, for instance from a fixed network form to anothercellular radio network form, and vice versa. The control unit 222performs call control, mobility management, collection of statisticaldata and signalling.

FIG. 2 further shows the mobile services switching centre 228 and agateway mobile services switching centre 230 which controls theconnections from the mobile communications system to the outside world,in this case to a public switched telephone network 232.

The solution according to the preferred embodiments of the invention canbe applied to both a base station receiver and a user equipmentreceiver.

Let us examine the example of a system model shown in FIG. 3. The modelis somewhat simplified, and it does not include, for instance, radiofrequency parts, antennas, chip pulse form scramblers and A/D convertersat transmission and reception ends, which are typically used in radiosystems. It is assumed in this example that the system uses both afrequency hopping (FH) technique and a direct-sequence (DS) technique.However, it is to be noted that the embodiments of the invention are notrestricted to this combination. Let us assume that binary data flow d(k)300 to be transmitted is coded by a turbo-coder 302 with a code rate 1/Rby using N_(e) parallel recursive systematic coders, each of which usesa code rate 1/R_(e) and which are separated from each other byinterleavers. Code bits are mapped with a BPSK method, and the symbollength is T_(b). Each data symbol b(kR+j), j=0, . . . , R−1 is thenmodulated in an DS-BPSK modulator 304 with a spreading code p(t) 306which is generated in a spreading code generator 308. The complexenvelope of a useful signal 310 before a FH modulator 310 is

$\begin{matrix}{{S_{T}(t)} = {\sum\limits_{k = 0}^{Q - 1}{\sum\limits_{j = 0}^{R - 1}{{b\left( {{kR} + j} \right)}{p\left( {t - {kRT}_{b} - {\left( {j - 1} \right)T_{b}}} \right)}}}}} \\{{= {\sum\limits_{k = 0}^{Q - 1}{\sum\limits_{j = 0}^{R - 1}{{b\left( {{kR} + j} \right)}{\sum\limits_{i = 0}^{N - 1}{c_{i}{u_{T_{c}}\left( {t - {iT}_{c} - {kRNT}_{c} - {\left( {j - 1} \right){NT}_{c}}} \right)}}}}}}},}\end{matrix}$where Q is the number of information bits per one frame, [b(kR),b(kR+1), . . . , b(kR+R−1)]=B_(k), where k=0, . . . , Q−1 is the codeword which is transmitted in the k:th information signalling time slotRT_(b), T_(c) is the chip time slot (i.e. the bit time slot of thespreading code), and which is proportioned to the signalling time slotT_(b) such that T_(b)=NT_(c), where N is processing gain. c=[c_(o), . .. , c_(N−1)]^(T) is the spreading sequence and u(t) is defined asfollows:

${u(t)} = \left\{ \begin{matrix}{\frac{1}{\sqrt{T_{c}}},} & {0 \leq t \leq T_{c}} \\{0,} & {elsewhere}\end{matrix} \right.$

A DS signal 310 is modulated in the FH modulator 312 where frequencyhops are generated according to a pseudo-random code 316 generated inthe FH generator 314.

The signal is transmitted to a channel 318 where interference and noise320 are added to the signal.

The signal that has passed through the channel is received in thereceiver, amplified in the radio frequency parts and passed to the FHdemodulator 322 where frequency hopping is decoded according to thepseudo-random code 326 generated in the FH generator 324.

Let us next examine the received signal in the output of the FHdemodulator 322. Then the signal has the formr(t)=Ae ^(jΦ) s _(T)(t−τ)+i(t)+w(t),  (1)where Ae^(jΦ) is the complex gain caused by the channel effect, τ is therandom delay caused by the channel and w(t) is thermal noise which canbe modelled as a complex Gaussian process with a power spectral density2N₀. i(t), for its part, is the complex envelope of the narrow-bandinterference signal.

Let us assume that the delay τ of the desired signal is either known orit is estimated. Then, the desired signal can be expressed in the

=(k+j):th signalling time slot of the code bit as a vector in anN-dimensional subspace from those functions in the space L²

T_(b)+τ, (

+1)T_(b)+τ[ whose quadratic absolute value can be integrated over theduration of T_(b). In the following, the marking S_(n)

and the term signal space are used for this subspace.

When the received waveform (1) is projected onto the selectedorthonormal base and the entire frame is observed, the followingNRQ-dimensional observation vector is obtained:r=[r ^(T)(1), . . . , r ^(T)

, . . . , r ^(T)(NRQ)]^(T),  (2)r

=Ae ^(jφ) b

s+i

+w

.s, i ja w indicate N-dimensional vectors of the projections of thedesired signal, interference and noise onto a suitable orthonormal base

of the signal space S_(n)

. s is proportional to spreading codes c. In the above, ( )^(T) refersto transpose.

An idea of the invention is that since the desired signal is of aspread-spectrum nature and the noise is uncorrelated, it is possible tofind an orthonormal conversion, whereby the desired signal has spreadevenly to all N components, whereas the narrow-band interference hasconcentrated on a subspace of the signal space, having small dimension.When a strong narrow-band interference has been received, some of theterms of r have an absolute value which is considerably higher than thatof others and by which they can be separated from the others, and thusinterference cancellation can be formed as a problem of finding theseunknown components. When these components have been found, their effectcan be reduced either by excising them to the desired level or bynullifying components. One embodiment is to include only those samplesin further processing whose absolute value is below the given limit.This alternative is called type I censoring. Another embodiment is tonullify L samples having the highest absolute values, where L is theestimate of the subspace dimension. This alternative is called type IIcensoring.

From the output of the FH demodulator 322, the signal is thus passed tointerference cancellation means 328 which perform the above describedprojection. After interference cancellation, DS-BPSK demodulation, i.e.the decomposition decoding 330 can be performed with a spreading codep(t) 332, which is generated in a spreading code generator 334. Thedecoded signal is passed to the turbo-decoder 336.

Another idea of the invention is that since the desired signal may alsohave components in the same direction as the narrow-band interference, amore accurate estimate for the interference is obtained, when theestimate of the desired signal is first subtracted from the receivedsignal, whereby the signal to be processed is such that the portion ofinterference and noise can be detected more easily. The subspacecomponents of the interference in this residual signal can be estimatedmore accurately. Thus, the signal is fed back from the turbo-decoder 336to the interference cancellation 328. The estimated signal is multipliedby the spreading code in a multiplier 338, before it is taken to theinterference cancellation.

Let us examine an example of the implementation according to a preferredembodiment of the invention by means of FIG. 4. The figure shows twoblocks, an interference cancellation block 400 and a decoder block 402.In the preferred embodiment of the invention, the decoder block isimplemented as a turbo-decoder. A decoder block of another type ispossible, too. From the previous iteration round, the received signal r

404 and the feedback soft decisions {circumflex over (b)}^(P) 406 aresupplied as input to the interference cancellation block from the outputof the turbo-decoder 402. These soft decisions are subtracted from thereceived signal. Before the subtraction, they must first be multipliedby the spreading code into a direct-sequence spread-spectrum form. Oneach iteration round, the interference cancellation block firstcalculates an orthonormal conversion U^(P), estimates the interferencesubspace Ŝ_(I) ^(P)

(i.e. the main direction for S_(I)

, and finally projects the signal onto the subspace Ŝ_(N) ^(P)

orthogonal to the interference subspace.

Let us examine the implementation of an orthonormal conversion a bitlater. Let the term z^(P)

refer to the absolute value vector of the vector {tilde over(r)}=[{tilde over (r)}^(P)(1), . . . , {tilde over (r)}^(P)

. . . , {tilde over (r)}^(P)(NRQ)]^(T), where{tilde over (r)}

=U ^(P) (r

−Ae ^(jΦ) {circumflex over (b)} ^(P)

s)  (3)and let z_({tilde over (r)}) ^(P)

refer to its ranked version, i.e.z ^(P)

=[z ₀ ^(P)

, . . . , z _(N−1) ^(P)

]^(T) =[|{tilde over (r)} ₀ ^(P)

|, . . . , |{tilde over (r)} _(N−1) ^(P)

|]^(T)z _({tilde over (r)}) ^(P)

=[z ₍₁₎ ^(P)

, . . . , z _((N)) ^(P)

]^(T),where z_((i)) ^(P) is the i:th grade statistics of z^(P)

, and {circumflex over (b)}^(P)

=sign [

{{tilde over (L)}^(P)

}] is the hard estimate of the code bit when {tilde over (L)}^(P)

is the soft output decoded from the interleaving of the turbo-decoder.According to formula (3), the estimate {circumflex over (b)}^(P)

of the desired signal, multiplied by the spreading code s, is thussubtracted from the received signal r

.

When L samples having the highest absolute values are nullified, we havea new data vector v^(P)

:v ^(P)

=G ^(P)

U ^(P) r

,   (4)where the censoring matrix G^(P)

is an N-dimensional quadratic diagonal matrix which depends on thereceived vector r

and is defined as follows:

$\begin{matrix}\begin{matrix}{{type}\mspace{14mu} I} & {G_{{{(l)}i},i}^{P} = \left\{ \begin{matrix}{1,} & {{{if}\mspace{14mu}{D_{i}(l)}} \geq {z_{(i)}^{P}(l)}} \\{0,} & {{{if}\mspace{14mu}{D_{i}(l)}} < {z_{(i)}^{P}(l)}}\end{matrix} \right.} \\{{type}\mspace{14mu}{II}} & {G_{{{(l)}i},i}^{P} = \left\{ {\begin{matrix}{1,} & {{{if}\mspace{14mu}{z_{({N - L})}(l)}} \geq {{{\overset{\sim}{r}}_{i}^{P}(l)}}} \\{0,} & {{{if}\mspace{14mu}{z_{({N - L})}(l)}} < {{{\overset{\sim}{r}}_{i}^{P}(l)}}}\end{matrix}.} \right.}\end{matrix} & (5)\end{matrix}$where D_(i)

indicates the suitable threshold values and L is the estimate of theinterference subspace Ŝ_(I) ^(P)

dimension. The superscript ( )^(P) indicates that the value of the termis from the previous iteration round. Type I and type II thus refer tothe earlier mentioned censoring methods of suppressing interference.Naturally on the first iteration round, no estimation results of theprevious iteration round are available, and then {circumflex over(b)}^(P)=0 can be used as initial values.

If the calculation needs to be made less complex, instead of softdecisions obtained from the decoder, hard decisions given by the decodercan also be used in calculating the censoring matrix G^(P)

. Then the censoring matrix is defined as follows:

$\begin{matrix}{{G_{{{(l)}i},i}^{P} = {G^{P}\left( \left\lfloor \frac{l}{R} \right\rfloor \right)}},{{\forall l} = 0},\ldots\mspace{11mu},{{QR} - 1},} & (6)\end{matrix}$where

$G^{P}\left( \left\lfloor \frac{l}{R} \right\rfloor \right)$is in accordance with formula (5) and └x┘ is the biggest integer, whichis not bigger than x.

Let us next examine the selection of the parameters, such as D and L,which are to be used in the calculation. It is also essential for thecalculation to define the base

of the orthonormal conversion. The interference cancellation is mosteffective, if the projection of a narrow-band interference signal in thesignal space comprises a limited number of components deviating fromzero. Therefore, the conversion base should be selected so that itfocuses the narrow-band interference on a subspace in the signal space,having small dimension.

In a preferred embodiment of the invention, the covariance matrix of thevector {tilde over (r)}^(P)

is estimated, where {tilde over (r)}^(P)

is based on N-dimensional data vectors r=[r(0), . . . , r(RQ−1)], whichare received during one frame, i.e.

$\begin{matrix}{{\hat{M}}_{{\overset{\_}{r}}^{P}{\overset{\_}{r}}^{P}}^{P} = {\frac{1}{RQ}{\sum\limits_{\ell = 0}^{{RQ} - 1}{{{\overset{\sim}{r}}^{PH}(l)}{{\overset{\sim}{r}}^{P}(\ell)}}}}} & (7)\end{matrix}$

By using eigenvalue value decomposition EVD, the orthonormal conversionU^(P) can be defined easily from the formula{circumflex over (M)}_({tilde over (r)}) _(p) _({tilde over (r)}) _(p)^(P)=U^(P)Δ^(P)U^(PH).where Δ denotes the singular value matrix. When this method is employed,on each iteration round a sample covariance matrix {tilde over (r)}^(P)

has to be calculated and its eigenvalue decomposition-has to beevaluated.

Another preferred embodiment of the invention utilizes the assumption ofthe interference having a narrow band, i.e. that its bandwidth issubstantially smaller than the bandwidth of the desired signal. TheFourier base can thus be selected as a base, i.e.

$\begin{matrix}{{{\Psi_{l}(t)} = {\frac{1}{\sqrt{N}}{\sum\limits_{m = 0}^{N - 1}{{u_{T_{c}}\left( {t - {mT}_{c}} \right)}{\exp\left( {{- j}\frac{2\pi\; m\; l}{N}} \right)}}}}},{l = 0},\ldots\mspace{11mu},{N - 1.}} & (8)\end{matrix}$

In this case, the orthonormal conversion corresponds to an N-point DFTconversion of the signal sampled from the output of the pulse formscrambler. When the received signal is corrupted by interference with afew frequency peaks only, this solution is particularly advantageous.

In a preferred embodiment of the invention, it is also essential todetermine the threshold values D_(i) and the interference spacedimension L mentioned in formula (5). If the eigenvalues obtained fromformula (7) are evaluated and a suitable information criterion, such asso-called Akaik (AIC), the smallest description length or an eigenvaluethreshold method, is used, the interference subspace S_(I)

dimension can be estimated adaptively. These information criteria areprior art methods, and the smallest mapping length, for instance, isexplained in the publication M.Wax, T.Kailath: “Detection of signals byinformation theroretic criteria”, IEEE Trans. Acoust. Speech, SignalProcessing, Vol. 33, pp. 387-392, 1985, which is incorporated herein asa reference. The parameter L can thus be set according to the dimension.

The threshold value D_(i), for its part, can in principle be set so thatit maximises the valuePr {|{tilde over (r)} _(m)

|>D _(m) |i≠0},i.e. the detection probability, provided that the false alarmprobabilityPr {|{tilde over (r)} _(m)

|>D _(m) |i=0}is fixed to a desired level. This maximisation can be calculated bymeans of a known likelihood test. This method requires, however, thedependence on the parameters of the interference signal, and it is notoptimal. In a preferred embodiment of the invention, a more intuitivesolution model is applied, where only the statistics of the term |{tildeover (r)}_(m)

| is utilized and a situation free of interference is assumed. When athreshold is set, it is essential to select them in such a manner thatthe signal is not censored unnecessarily when the interference is weakand yet so that the interference cancellation is ensured when theinterference is strong. Let us assume that the eigenvalue E[{circumflexover (b)}

w

i=0]=0; as a result, when the conditions of {circumflex over (b)}

of b

and when i=0 and when |r_(m)|² is the non-centralised variable of the χ²distribution, having two degrees of freedom, thenE[|{tilde over (r)} _(m)|² |i=0]=A ₀ ² |s _(m)|² E[(1−{circumflex over(b)}

)²]+2N ₀Var[|{tilde over (r)} _(m)|² |i=0]=4N ₀+4N ₀ A ₀ ² E[(1−{circumflex over(b)}

)² ]|s _(m)|²,where E[(1−{circumflex over (b)}

)²]=(2−2E[b

{circumflex over (b)}(l)])=(2−2 sign[{tilde over (Λ)}^(P) (l)] tanh[½[{tilde over (Λ)}^(P)

]).

Let us examine the example of the implementation according to thepreferred embodiment of the invention, which was already partlyexplained and shown in FIG. 4. The figure thus shows two blocks, theinterference cancellation block 400 and the decoder block 402 which ispreferably, but not necessarily, a turbo-decoder. From the previousiteration round, the received signal 404 and the feedback soft decisions406 are supplied as input to the interference cancellation block 400from the output of the turbo-decoder 402. On each iteration round, anupper calculating unit 408 of the interference cancellation block 400first determines an estimate for the narrow-band interference propertiesby subtracting the estimate obtained from the output of theturbo-decoder from the received signal. Then an orthonormal conversionU^(P) is calculated on the basis of formulas (7) or (8), for instance,and the interference subspace Ŝ_(I) ^(P)

is estimated from the residual signal. Then the upper calculating unitdefines the censoring matrix G^(P) on the basis of formula (5), forinstance.

The information on the orthonormal conversion and censoring matrix istransmitted to a lower calculating unit 410 where the actual censoringis performed and the new data vector v^(P)

according to formula (4) is calculated. This data vector is passed tothe turbo-decoder 402 as input.

Both calculating means 408, 410 of the interference cancellation block400 can preferably be implemented programmatically by means of aprocessor and a suitable program or also as an ASIC circuit or by meansof separate logic circuits. It is to be noted that the interferencecancellation block can also be implemented by means of one or morecalculating units and the implementation described herein is only anexample, as is obvious to a person skilled in the art.

The turbo-decoder 402 comprises a SISO (soft-in soft-out) decoder. Theturbo-decoder comprises two parallel-concatenated decoders 412, 414,between which interleaving 416, 418 is performed. The decoding is basedon decoding the component codes alternately and transmitting so-calledextrinsic information, which is a part of the soft output of the SISOdecoder, to the next decoding stage. The signal can be iterated severaltimes in the turbo-decoder by re-feeding the obtained estimates 420 tothe decoder. The deinterleaving 422 of is performed therebetween. Theoutput of the turbo-decoder is fed back 406 to the interferencecancellation block, and the loop also includes the deinterleaving 424.The decoder can also comprise a control block 426 controlling thefunction of different parts of the decoder. If several iteration roundsare performed in the decoder, the control block 426 gives a command tostop the iteration and transmits the estimates further to theinterference cancellation block. The estimates are also taken further toother parts 428 of the receiver. The iteration can also be controlledfrom outside the decoder at a higher level of the receiver.

On the P:th iteration round, the decoder makes a decision on thetransmitted bits on the basis of the vector v^(P), which has the formv ^(P) =[v ^(PT)(1), . . . , v ^(PT)

. . . , v ^(PT)(NRQ)]^(T) =G ^(P) U ^(P) r,where v^(P)

is obained from formula (4) and G^(P)U^(P) is an NRQ-dimensional matrixwhich has the formG ^(P) U ^(P)=diag (G ^(P)(0)U ^(P) , . . . , G ^(P)(RQ)U ^(P)).

For the sake of clarity, the term

{{Y_(h)^(P)(k)}_(k = 0)^(Q − 1)}_(h = 0)^(N_(e) − 1)refers in the following to an NR_(e)-dimensional vector which has theform(k)=[v ^(PT)(k),v ^(PT)(k+hR _(e)+1), . . . , v ^(PT)(k+(h+1)R_(e)−1)]^(T),h=0, . . . , N _(e)−1 k=0, . . . , Q−1.

In the definition of the decoder, let us assume that there is nointerference in the output of the decoder. There are two reasons forthis: firstly, this ensures that if the censoring has been completelysuccessful, the remaining samples can be processed optimally. Secondly,if the interference signal is weak, the loss that formula (5) has causedin the signal, compared to the conventional decoder processing theoriginal received signal, is minimised.

The soft decision on the i:th Map decoder is obtained as a logarithm ofthe APT (a posteriori likelihood) ratio of each information bit d_(k)=1compared to APT=0. Thus the soft decision has the form

${L_{h}^{P}\left( d_{K} \right)} = {\log{\frac{\sum\limits_{m}{\sum\limits_{m^{\prime}}{{\gamma_{1}\left( {{Y_{h}^{P}(k)},m^{\prime},m} \right)}{\alpha_{k - 1}\left( m^{\prime} \right)}{\beta_{k}(m)}\text{)}}}}{\sum\limits_{m}{\sum\limits_{m^{\prime}}{{\gamma_{0}\left( {{Y_{h}^{P}(k)},m^{\prime},m} \right)}{\alpha_{k - 1}\left( m^{\prime} \right)}{\beta_{k}(m)}\text{)}}}}.}}$

Forward and backward recursions of the Map decoder can be expressed asfollows:

${\alpha_{k}(m)} = {{const}_{\alpha}{\sum\limits_{m^{\prime}}{\sum\limits_{i = 0}^{1}{{\gamma_{i}\left( {{Y_{h}^{P}(k)},m^{\prime},m} \right)}{\alpha_{k - 1}\left( m^{\prime} \right)}}}}}$${\beta_{k}(m)} = {{const}_{\beta}{\sum\limits_{m^{\prime}}{\sum\limits_{i = 0}^{1}{{\gamma_{i}\left( {{Y_{h}^{P}(k)},m^{\prime},m} \right)}{\beta_{k - 1}\left( m^{\prime} \right)}}}}}$where const_(α) ja const_(β) are constants caused by normalisation.Transition probability γ_(i)( ), where i=0,1, is, for its part, isobtained in the following manner:Γ_(i)(Y _(h) ^(P() k),m,m′)=Prob(Y _(h) ^(P)(k)|d _(k) =i, S _(k) =m, S_(k−1) =m′)Prob(d _(k) =i, S _(k) =m, |S _(k−1) =m′).

Following the earlier mentioned publication of M. Lops and A. Tulino andits markings, the above mentioned formula for both type I and type IIcensoring can be expressed in the following form:

$\begin{matrix}{{\gamma_{i}\left( {{Y_{h}^{P}(k)},m,m^{\prime}} \right)} = {{{Prob}\left( {d_{k} = i} \right)}{Prob}\left( {S_{k + 1} = {{m^{\prime}❘S_{k}} = m}} \right){\sum\limits_{n = 1}^{Q}{{g\left( {{v_{1}},\ldots\mspace{11mu},{v_{N}},{q = q^{(n)}}} \right)} \times {\prod\limits_{j = 0}^{R - 1}{\exp\frac{\left( {{v^{P}\left( {k + {\left( {h - 1} \right)R_{e}} + j} \right)} - {{G^{P}\left( {k + {\left( {h - 1} \right)R_{e}}} \right)}U\; A\;{\mathbb{e}}^{j\phi}}} \right.^{2}}{2N_{0\;}}}}}}}} & (9)\end{matrix}$where q^((n)) is a variable having Q possible values representing then:th censoring event where Q=2^(N) for type I censoring and Q=N! fortype II censoring. It is to be noted that the term g(|ν₁|, . . .,|ν_(N)|,q=q^((n))) does not depend on the code bit b

and is clearly a constant term, which is removed in the reliabilitycalculation. The first term of formula (9), a priori information on thetransmitted information bits, is a function of the external L_(ext)information. A reference is herein made to the publication P. Robertson,Illuminating the Structure of Code and Decoder of Parallel ConcatenatedRecursive Systematic (Turbo) Codes, Proc. Globecomm '94, December 1996.As appears from the presented formula (9), in connection with the metriccalculation, filtering adapted to the spreading code, i.e. DSdecomposition decoding, is also performed. This is indicated by the terms in formula (9). In order to operate the presented LogMap algorithmrequires the information on the signal-to-noise ratio. If the estimateof the signal-to-noise ratio is not available, a so-called SOVAalgorithm known to a person skilled in the art can be applied. Thepublication W. Feng, B. Vucetic, A List Bidirectional Soft OutputDecoder of Turbo Codes, International Symposium on Turbo Codes, Brest,France, 1997 is given as an example of this. The branch metric for bothcensoring types is as follows:

${\lambda_{h}^{P}\left( d_{k} \right)} = {{- 2}{\sum\limits_{j = 0}^{R - 1}{\mathcal{R}\left\{ {A\;{\mathbb{e}}^{j\Phi}s^{H}U^{PH}{v\left( {k + {\left( {h - 1} \right)R_{e}} + j} \right)}} \right\}}}}$where ( )^(H) refers to conjugate transpose.

Let us examine an example of an embodiment of the invention by means ofthe flow chart of FIG. 5 a. A signal is received in step 500. In step502, a default value, for example 0, is determined for the estimates ofthe desired signal for the first round of the interference cancellationiteration. In step 504, the estimate is subtracted from the receivedsignal. In step 506, an interference subspace is defined and itssignificance in the received signal is reduced. In step 508, turbodecoding is performed and the estimates for the desired signal aredetermined. These estimates are passed back to the interferencecancellation 510.

Flow chart 5 b shows another example. The chart is otherwise similar tothe previous one, but after the turbo decoding, a decision is made instep 512, whether a new iteration is performed for the decoding. If not,the estimates 510 are passed to the interference cancellation, if yes,the estimates 514 are passed to the input of the decoder again.

Although the invention has been described above with reference to theexamples according to the attached drawings, it is obvious that theinvention is not restricted thereto, but may be modified in a variety ofways within the scope of the inventive idea disclosed in the attachedclaims.

1. An apparatus, comprising an input signal comprising a received signaland an estimate for the received signal, a calculating unit configuredto perform an orthonormal conversion of the received signal intosubspace components of a desired subspace and to determine an estimatefor narrow-band interference properties, in which the determination ofthe estimate obtained from the received signal is subtracted from thereceived signal before the orthonormal conversion is performed, and aninterference canceller configured to suppress the subspace componentscomprising narrow-band interference signals from the received signal byusing the determined estimate, and to excise the subspace componentsthat are stronger than a given threshold from the received signal to adesired level and to suppress the subspace components comprisingnarrow-band interference signals from the received signal.
 2. Theapparatus as claimed in claim 1, wherein the apparatus comprises aturbo-decoder.
 3. An apparatus, comprising an input signal comprising areceived signal and an estimate for the received signal, means forperforming an orthonormal conversion of the received signal intosubspace components of a desired subspace and determining an estimatefor narrow-band interference properties, in which the determination ofthe estimate obtained from the received signal is subtracted from thereceived signal before the orthonormal conversion is performed, andmeans for suppressing the subspace components comprising narrow-bandinterference signals from the received signal by using the determinedestimate, and excising the subspace components that are stronger than agiven threshold from the received signal to a desired level and tosuppress the subspace components comprising narrow-band interferencesignals from the received signal.
 4. An integrated circuit, comprisingan input signal comprising a received signal and an estimate for thereceived signal, a calculating unit configured to perform an orthonormalconversion of the received signal into subspace components of a desiredsubspace and to determine an estimate for narrow-band interferenceproperties, in which the determination of the estimate obtained from thereceived signal is subtracted from the received signal before theorthonormal conversion is performed, and an interference cancellerconfigured to suppress the subspace components comprising narrow-bandinterference signals from the received signal by using the determinedestimate, and to excise the subspace components that are stronger than agiven threshold from: the received signal to a desired level and tosuppress the subspace components comprising narrow-band interferencesignals from the received signal.
 5. A base station, comprising an inputsignal comprising a received signal and an estimate for the receivedsignal, a calculating unit configured to perform an orthonormalconversion of the received signal into subspace components of a desiredsubspace and to determine an estimate for narrow-band interferenceproperties, in which the determination of the estimate obtained from thereceived signal is subtracted from the received signal before theorthonormal conversion is performed, and an interference cancellerconfigured to suppress the subspace components comprising narrow-bandinterference signals from the received signal by using the determinedestimate, and to excise the subspace components that at stronger than agiven threshold from the received signal to a desired level and tosuppress the subspace components comprising narrow-band interferencesignals from the received signal.
 6. User equipment, comprising an inputsignal comprising a received signal and an estimate for the receivedsignal, a calculating unit configured to perform an orthonormalconversion of the received signal into subspace components of a desiredsubspace and to determine an estimate for narrow-band interferenceproperties, in which the determination of the estimate obtained from thereceived signal is subtracted from the received signal before theorthonormal conversion is performed, and an interference cancellerconfigured to suppress the subspace components comprising narrow-bandinterference signals from the received signal by using the determinedestimate, and to excise the subspace components that are stronger than agiven threshold from the received signal to a desired level and toSuppress the subspace components comprising narrow-band interferencesignals from the received signal.
 7. A method of suppressing narrow-bandinterference from a wide-band signal, comprising: receiving a signal,performing, by a processor, an orthonormal conversion of the receivedsignal into subspace components of a desired subspace, decoding theconverted signal with a decoder, in which an estimate for the receivedsignal is obtained, determining, by a processor, an estimate fornarrow-band interference properties by subtracting the estimate obtainedfrom an output of the decoder from the received signal before performingthe orthonormal conversion, suppressing, by a processor, the subspacecomponents comprising narrow-band interference signals reduced in thereceived signal by means of the determined estimate, and excising, by aprocessor, the subspace components that are stronger than a giventhreshold from the received signal to a desired level to generate aninterference suppressed signal.
 8. The method as claimed in claim 7, themethod further comprising suppressing the subspace components thatcomprise harrow-band interference signals from the received signal. 9.The method as claimed in claim 7, the method further comprising passingthe interference suppressed signal to the decoder again, and performinginterference cancellation as many times as desired.
 10. The method asclaimed in claim 7, the method further comprising passing theinterference suppressed signal through the decoder several times beforethe output of the decoder is used in the interference cancellation.